Interpreting Results from FieldDeployments of SemipermeableMembrane DevicesJ E F F L O U C H , * , † G I N N Y A L L E N , †

C A T H Y E R I C K S O N , †

G L E N N W I L S O N , ‡ A N DD A V E S C H M E D D I N G ‡

National Council for Air and Stream Improvement, Inc.(NCASI), P.O. Box 458, Corvallis, Oregon 97339, andDepartment of Environmental and Molecular Toxicology(formally NCASI), Oregon State University,Corvallis, Oregon 97331

Three canisters of semipermeable membrane devices(SPMDs), each containing five SPMDs, were deployed atthree different locations on a transect across a small riverremoved from the impact of near-field point sources.Following a 62-day deployment, the masses of variouspolynuclear aromatic hydrocarbons (PAH) sequestered byeach SPMD in each canister were determined. Thecompound-specific mean residues (ng/SPMD) obtainedfor the PAHs with pKow values >4.4 showed statisticallysignificant (R ) 0.10) differences between the threedeployment locations (canisters) ranging from approximately10 to 160 ng/SPMD, corresponding to relative percentdifferences (RPDs) ranging from 10% to 54%. There wereno statistically significant differences between thesame three locations for the single PAH with a pKow<4.4. A detailed discussion of how different (uncontrollable)environmental variables may have impacted the experimentalresults is provided to illustrate the uncertainties associatedwith interpreting the results from SPMD field deploymentsand highlight the need for some means of correcting forthese impacts. The results from this work also illustrate theneed to account for spatial variability in water columnconcentrations (i.e., sample heterogeneity) as part of anyinterpretation.

IntroductionSemipermeable membrane devices (SPMDs) are passivesampling devices that are increasingly finding applicationfor the characterization of nonpolar chemicals in aquaticsystems. Huckins and co-workers pioneered the developmentof this tool and have generated many publications providingtheory addressing the use of SPMDs for making quantitativeconcentration measurements (1-4). These researchers havealso thoroughly discussed both the theoretical and thepractical limitations of SPMDs in these applications (1, 2).

A number of workers have used SPMDs to characterizechemical gradients in receiving waters (5-11). Although thepotential impacts of biofouling, temperature, and flowvelocity (i.e., “environmental” variables) on SPMD uptake

rates are usually acknowledged, the SPMD data have oftenbeen interpreted without any attempts to correct or otherwiseaccount for the impact of these variables on SPMD residues.In addition, results from a single SPMD (or a single set ofSPMDs) are often interpreted as reflecting the chemicalconcentrations of large volumes of water [e.g., in theColumbia (8), Androscoggin (10), Kennebec (10), and ClinchRivers (11)] without any attempts to account for the spatialvariability (i.e., sample heterogeneity) of chemical concen-trations within the water column. This is of particular concernas many of these discussions have focused on the impact orrelevance of point sources.

In this study, three sets of SPMDs were deployed on atransect across a small channelized river removed from theimpacts of near-field point sources. This specific site wasselected because it represents the type of system for whichmany researchers might rationally assume that a single SPMD(or a single set of SPMDs) would be sufficient to characterizethe concentration of a given chemical at all points in thewater column (e.g., at a specific river mile). Three sets ofSPMDs were placed across this river simply to see if thisassumption could be supported and to characterize themagnitude of the potential inter-location differences thatmight manifest. As part of these deployments, flow velocityand temperature were monitored at each of the threedeployment locations in order to assess the possibility thatthese factors contributed to any observed inter-locationdifferences, and the results are discussed in light of thesedata.

Materials and MethodsSPMDs and Stainless Steel Deployment Canisters. TheSPMDs used in this study were purchased from Environ-mental Sampling Technologies (EST, St. Joseph, MO). TheseSPMDs represent what Huckins et al. have termed the“standard” SPMD (2, 3). SPMDs were received from EST insealed paint cans already loaded on EST-supplied SPMD“spiders”, and EST-supplied stainless steel “canisters” wereused in the field deployment.

Deployment Site. SPMDs were deployed on the Long TomRiver in Oregon’s Willamette Valley. This river acts as theoutfall for Fern Ridge Reservoir, which largely drains OregonCoast Range forest land and is used for recreation, irrigation,and flood control. The Long Tom River has been extensivelychannelized and is heavily used for farmland irrigation. Waterlevels in the river are controlled by the upstream reservoirto maintain irrigation volume. River levels are historicallymaintained too low to conceal samplers during the springand summer months, so deployment was timed to coincidewith the initiation of the annual lowering of the headwaterreservoir in October, which serves to increase the flow bymore than an order of magnitude within a 30-day period.

The SPMDs were deployed on a transect across the LongTom River at a point approximately 0.5 mi below BundyBridge at the first sharp curve eastward. The only point sourceon the river is the Monroe municipal outfall, which isapproximately 6.5 mi upstream from the Bundy Bridgedeployment site. This site was selected because it seemedreasonable to assume that all “dissolved” chemicals wouldbe well mixed.

SPMD Deployment. Three stainless steel canisters weredeployed on a transect across the Long Tom River. Eachcanister contained five standard SPMDs and three VemcoMinilog TR remote temperature loggers (Vemco Limited,Shad Bay, Nova Scotia), which were set to take measurementsevery 15 min during the deployment period. All three canisters

* Corresponding author e-mail: JLouch@ncasi.org; telephone:(541)752-8801; fax: (541)752-8806.

† National Council for Air and Stream Improvement, Inc. (NCASI).‡ Oregon State University.

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were left in the Long Tom for 62 days from October 17 toDecember 18, 2000.

SPMD canisters were located ≈10 ft out from each bankand at approximately the middle of the river, which is about80 ft wide at the deployment site. Each canister was situatedapproximately 2 ft from the river bottom, anchored withweights, and oriented vertically with Styrofoam floats. SPMDswere loaded into the canisters at the sampling site, and a tripblank SPMD was exposed to the atmosphere during deploy-ment and recovery of the SPMDs. Immediately prior todeploying the SPMDs, flow measurements were made at eachof the three deployment locations using a Gurley PrecisionInstruments Pygmy Meter (model D625, with a model 1100flow velocity indicator). Measurements of flow inside theSPMD canisters were also made. During the deploymentperiod, additional flow measurements were made at days15, 29, 45, and 62.

Chemical Analyses. On retrieval from the Long Tom River,all the SPMDs were removed from the canisters, sealed inpaint cans, and placed in a freezer. The next day, these paintcans were shipped to EST for generic dialysis/extraction(including cleaning of the SPMDs prior to dialysis), and thehexane dialysates (≈4 mL of hexane sealed in glass ampules)were returned to NCASI for analysis along with a dialysisblank.

On return to NCASI, each hexane (SPMD) dialysate/extractwas analyzed to determine 20 polynuclear aromatic hydro-carbons (PAHs). Briefly, half of each hexane (SPMD) dialysate/extract was concentrated to approximately 0.5 mL and thendiluted up to 4.5 mL with dichloromethane (DCM). Gelpermeation chromatography (low-pressure GPC with SX-3Bio-Beads) was then used to remove residual “lipid” fromthe extracts. The resulting DCM cut (from the baseline at theleading edge of methoxychlor to the baseline at the leadingedge of sulfur) was concentrated, transferred into 200 µL oftoluene, and fortified with 2-fluorobiphenyl, phenanthrene-d10, and chrysene-d12 as internal standards. Subsequently, 2µL of this final extract was analyzed by selected ion monitoring(SIM) GC/MS (HP 5972 with a 30 m × 0.25 mm 0.25 µmRTX-5 column), and the PAHs quantified versus either 3- or4-point calibrations.

ResultsDeployment Conditions. Deployment Temperature. Figure1 is a plot showing the outputs of three of the miniloggers,one from each SPMD canister, over the 62-day deploymentperiod. Although the temperatures recorded by these minilog-gers ranged from a low of 4.8 °C (the low end of the device’srange) to a high of 15 °C, the plots in Figure 1 suggest thatthe temperatures at the three sites tracked each other almostexactly. This impression was borne out by statistical analysis,which showed that the mean readings from the multipleminiloggers were statistically indistinguishable (R ) 0.0001).Thus, temperature was not a source of inter-site bias in thisstudy, and the overall mean deployment temperature was11.35 °C (this estimate is likely biased high due to thetemperature dropping off scale for periods).

Flow Velocity. Table 1 summarizes all flow velocitymeasurements made over the course of the 62-day deploy-ment. Over this period, measured flows outside the SPMDcanisters ranged from 0.23 to 1.02 m/s, while measured flowsinside the SPMD canisters ranged from 0.14 to 0.44 m/s. Onaverage, the measured flow velocities inside the canisterswere about half that measured outside the canisters.

In general, the highest flow velocities were observed atthe mid-channel (center) deployment location. The averageflows inside the SPMD canisters at the three deploymentlocations were 0.23 m/s at the west location, 0.32 m/s at thecenter location, and 0.27 m/s at the east location. Thedifference between the west and the center locations wasstatistically significant at the 90% confidence level, while thedifferences between the center and east and the east andwest locations were not (p ) 0.22 and 0.26, respectively).

Biofouling. EST reported that all the SPMDs exhibited“light” biofouling. Although this subjective judgment is usefulfor characterizing the relative degree of biofouling, it is notsufficient to determine if there were any real trends inbiofouling between sites. Thus, the potential impact of site-to-site differences in biofouling on the SPMD residuesobtained in this study cannot be characterized.

SPMD Residues. Following analysis of all the individualSPMD extracts, those PAHs giving SPMD residues within a

FIGURE 1. Temperatures recorded by representative temperature loggers (one from each SPMD canister) over the course of the 62-daydeployment (temperature recorded every 15 min).

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factor of 5 of those found in the associated trip blank SPMDor dialysis/method blank were dropped. Of the remaininganalytes, three gave mean residues (ng) less than the analyte-specific lower calibration levels (nominally 10-20 ng) andso were also excluded from further consideration. Table 2gives the results for the remaining nine PAHs in terms ofmass (ng) of chemical quantified in the analytical extracts(which corresponds to half the total mass sequestered byeach SPMD).

From Table 2, the relative standard deviations (RSD) foreach chemical at each site provide a measure of variabilityover the experimental process from deployment throughanalysis. These RSDs range from 4.5% (9-methylphenan-

threne in the east canister) to 33.1% (pyrene in the mid-channel canister), and the overall mean RSD (nine chemicalsin three sets of SPMDs gives n ) 27) was 12.0% ( 8.3%. Thesenumbers are consistent with the precision reported by otherworkers from both laboratory (12) and field (7) deploymentsof SPMDs and reflect a combination of SPMD to SPMDdifferences in analyte uptake under identical conditions andgeneral analytical variability.

Scatter plots were generated for each PAH, and Figure 2gives four examples. Eight of nine of these plots suggesteda trend toward greater SPMD residues from east to west,with acenaphthylene being the only exception. Althoughthese plots suggest the potential presence of some outliers,

TABLE 1. Flow Velocities Measured Inside and Outside the SPMD Canisters Placed at Three Deployment Locations

west site center site east site

dayexternala

(m/s)internalb

(m/s)internal/

external (%)externala

(m/s)internalb

(m/s)internal/

external (%)externala

(m/s)internalb

(m/s)internal/

external (%)

0 0.75 0.33 44 1.03 0.44 43 0.85 0.33 3915 0.77 0.25 32 1.02 0.22 22 0.77 0.40 5229 0.23 0.14 61 0.48 0.29 60 0.39 0.25 6545 0.25 0.14 56 0.29 0.22 76 0.29 0.14 4862 0.4 0.28 70 0.81 0.44 54 0.85 0.22 26

mean 0.48 0.23 53 0.73 0.32 51 0.63 0.27 46SD 0.26 0.09 15 0.33 0.11 20 0.27 0.10 15RSD 55 37 28 46 35 40 43 37 32

a Flow in m/s measured outside SPMD canister. b Flow in m/s measured inside SPMD canister.

TABLE 2. Mass of PAHs Recovered from SPMD Extracts

SPMD extractresidue (ng)b

significantly differentgroups (p e 0.10)c

significantdifferencesd

analyte pKowa canister location mean SD % RSD A B C mass (ng) RPD (%)

acenaphthylene 4.08 east 9 1.3 14 xcenter 11 3.5 32 xwest 10 0.5 5 x

phenanthrene 4.46 east 253 17 7 xcenter 267 15 6 x x 28e 10e

west 281 16 6 x

2-methylphenanthrene 4.86 east 60 3.7 6 xcenter 64 7.2 11 x 11 16west 73 6.4 9 x

9-methylphenanthrene na east 31 1.4 4 xcenter 32 4.2 13 x 5 15west 37 4.0 11 x

1-methylphenanthrene 5.08 east 73 3.1 4 xcenter 70 6.2 9 x 14 18west 85 7.5 9 x

3-methylphenanthrene 5.15 east 32 1.6 5 xcenter 34 3.5 10 x 6 17west 39 3.7 10 x

fluoranthene 5.2 east 136 33 24 x 33f 17f

center 178 20 11 x 42f 27f

west 211 20 10 x 75f 43f

pyrene 5.3 east 111 35 31 xcenter 105 34 33 x 80 54west 188 20 10 x

chrysene 5.61 east 25 2.1 8 xcenter 27 4.3 16 x 9 30west 35 3.5 10 x

a pKOW values as reported by Huckins et al. (12) except for 1-, 2-, and 3-methylphenanthrene, which are from Howard and Meylan (13) (a pKOW

for 9-methylphenanthrene was not available). b Mean residue (ng) found in the replicate extracts from SPMDs placed at each of the three experimentallocations; n ) 5 for the center and west locations, n ) 4 for the east location (one replicate from the east location was lost in preparation). (Notethat only half of each extract was analyzed, so “whole” SPMD residues are 2× the mass listed.) c Locations identified by the ANOVA as beingstatistically distinct from the other locations are assigned a unique “group” label (A, B, or C), while those not determined to be statistically differentare assigned to the same group. d Differences between groups identified by ANOVA. e Differences between east and west canisters. f Smallestto largest differences (center-west, east-center, east-west).

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the results obtained from an ANOVA (analysis of varianceusing means assuming uniform variance) agreed with thoseobtained from application of the Kruskal-Wallis test (anonparametric analysis of variance using medians, which isless sensitive to outliers), with the single exception ofphenanthrene. In the case of phenanthrene, the ANOVAidentified statistically significant (R ) 0.10) differences inthe residues from the three locations, but the Kruskal-Wallistest did not deem these differences significant (they were,however, significant at R ) 0.12). Inspection of Figure 2 showsno indication of an outlier in the phenanthrene data, and sothe results from the ANOVA are used as the metric charac-terizing statistical significance for all the PAHs (note that allreplicates were included in these analyses).

In cases where statistically significant differences wereobserved, the average relative percent differences (RPDs)were calculated using the means from like locations (asidentified by the ANOVA). From Table 2, these RPDs rangedfrom 10.5% (the difference between phenanthrene at theeast and west locations only) to 54% (pyrene), and the averageRPD (n ) 10) was 24.8% ( 14.0%.

DiscussionAs noted, statistically significant differences were observedbetween SPMD residues from different locations for all butone of the PAHs measured in this study. Determining if thesedifferences reflect true differences in water column con-centrations or simply differences in SPMD uptake rates atthe three locations resulting from differences in location-specific conditions, is a matter open to discussion.

Case for Site-Specific Conditions. As discussed byHuckins et al. (1), SPMD uptake rates for “low” pKOW

chemicals are limited by diffusion in the SPMD mem-brane (i.e., SPMD uptake is membrane controlled). AspKOW increases, the rate-limiting step in SPMD uptakeswitches from diffusion in the membrane to diffusion in thebulk water phase. Thus, the uptake of low pKOW chemicalsis less susceptible to variations in facial flow velocity (velocityat the surface of the SPMD membrane) than the uptake ofhigh pKOW chemicals. This suggests that comparisons of theSPMD residues of the lower pKOW PAHs might serve as acheck on the assumption of homogeneous concentrationsin this study. If this assumption can be validated for the lowpKOW PAHs, it would support environmental factors ascontributing to the trends observed for the higher pKOW

PAHs.Huckins et al. (1) estimated that the switch between

membrane-controlled and bulk water diffusion-controlledSPMD uptake occurs at pKOW ≈ 4.4. From Table 2, acenaph-thylene is the only experimental PAH with a pKOW <4.4, andit gave statistically indistinguishable SPMD residues at thethree locations. If it is assumed that this chemical is aneffective surrogate for the other PAHs, this outcome suggeststhat the dissolved water column concentrations were thesame at all three locations during the course of the SPMDdeployment. This conclusion is not challenged by the factthat significant differences in SPMD residues were observedfor the higher pKOW PAHs simply because theory predictsthat SPMD uptake of these chemicals will be more sensitiveto differences in flow velocity.

FIGURE 2. Scatter plots showing SPMD residues for four of the experimental PAHs from the three deployment locations at the singledeployment site. The error bars in these plots show the mean ( one standard deviation. Note that because only half of each SPMD extractwas analyzed, the results reflect half the mass that would have been recovered if the full extract had been analyzed.

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An alternate approach is to consider those chemicals thatreached equilibrium (i.e., steady-state) with the SPMDs tobe probes characterizing the consistency of dissolved con-centrations from location to location. The rationale for thisis that the primary environmental factor that might impactthe SPMD-water partition coefficient (KSPMD) of these PAHsis temperature (1), which was identical at all three locations.The other environmental variables (flow velocity and bio-fouling) will impact the time required to reach a chemical-specific equilibrium but should not have any impact on KSPMD

and thus the mass of chemical sequestered by an SPMD atequilibrium. Thus, differences in SPMD residues (for chemi-cals at equilibrium) between the three locations would notbe expected to manifest if dissolved concentrations weretruly the same at the three deployment locations regardlessof subtle inter-location differences in flow or biofouling.

The time required for an SPMD to reach chemical-specificequilibrium with the water column is related to a chemical’sKSPMD, which is, in turn, related to its KOW (2). In general, thehigher the KOW, the longer the time required to reachequilibrium. The other factor controlling the time to equi-librium is the chemical-specific SPMD sampling rate (RS),which is usually expressed in units of liters per day (2). Ifchemical-specific values of KSPMD and RS are available, achemical-specific SPMD “half-life” (i.e., t1/2) can be calculatedaccording to the following relationship (2):

This t1/2 is the time required for an SPMD to reach 50% ofequilibrium, and linear uptake is expected up to this point(14). After this period, SPMD uptake decreases as partitioningof the chemical into the SPMD approaches equilibrium, andattainment of full equilibrium (steady-state) requires de-ployment periods >4 times t1/2 (2).

Huckins et al. (12) published experimental values of KSPMD

and RS for a number of the PAHs measured in this study. Thevalues were used to estimate chemical-specific values of t1/2

according to eq 1, and these are listed in Table 3 along withHuckins et al.’s values of KSPMD and RS. According to Huckinset al. (2, 12), KSPMD can also be estimated from a chemical’striolein-water (KTW) and membrane-triolein (KMT) partitioncoefficients or from KTW and the chemical-specific mem-brane-water (KMW) partition coefficient. Booij et al. (15)reported regression models for estimating KTW and KMT fromKOW. Hofmans (16) also reported a regression model forestimating KTW from KOW as well as a regression model forestimating KMW from KOW. These relationships were used toestimate the appropriate partition coefficients for the ex-perimental PAHs, which were then used to estimate KSPMD

and t1/2. These values are also listed in Table 3.

The values for t1/2 listed in Table 3 indicate that acenaph-thylene was the only chemical clearly at equilibrium at 62days. Thus, as noted, environmental factors should not havecontributed any bias to the inter-location comparisons, soany trends observed can only be attributed to true differencesin water column concentrations between the three deploy-ment locations. From Table 2, there were no statisticallysignificant differences between locations for acenaphthylene,indicating uniform concentration of this chemical. Extensionof this conclusion to the other PAHs is not challenged by thefact that significant differences in SPMD residues wereobserved for the higher pKOW PAHs simply because thesechemicals were still in the linear portion of their respectiveuptake curves and thus were still susceptible to variability/bias resulting from environmental factors (e.g., biofouling).

If it is accepted that the differences observed betweendeployment locations in this study resulted from environ-mental factors, the results highlight the need to account forthese factors in interpreting the results from field deploy-ments of SPMDs. Since intra-canister SPMD replicates usuallygive good overall precision (i.e., the sum of analytical andintra-canister “deployment” variability), fairly small differ-ences between sites can be judged to be statisticallysignificant. In this study, the average intra-canister RSD wasnominally 12% (including laboratory analytical variability),and this was sufficient to identify (by ANOVA) statisticallysignificant inter-canister differences ranging from approxi-mately 10% to 54% (expressed as RPDs). Considering thatthe combination of flow velocity, temperature, and biofoulingcan result in inter-site bias exceeding an order of magnitude(1), only the grossest of inter-site differences will be at-tributable to anything but environmental variables in theabsence of extensive data discounting these factors or,alternatively, implementation of some type of correctionaccounting for them. At this time, the only proposed meansfor doing this appears to be the inclusion of appropriatepermeability/performance reference compounds (PRC) (1)as part of SPMD field deployments. However, despite recentreports in the literature (1), the effectiveness of PRCs for thispurpose has not yet been rigorously demonstrated.

Case for a Concentration Gradient across the ThreeDeployment Sites. As noted, the scatter plots suggestedtrends toward greater SPMD residues east to west for all ninePAHs except acenaphthylene (Figure 2), and these trendswere supported by statistical analysis (Table 2). Since therewere no statistically significant differences in deploymenttemperatures observed between the three locations, thesetrends cannot be attributed to trends in temperature. Inaddition, the subtle differences apparent in the flow velocitymeasurements (Table 1) suggest that flow velocity was lessat the location that gave the greatest SPMD residues (the

TABLE 3. SPMD Sampling Rates (RS), KSPMD Values, and Estimated Half-Lifes for Experimental PAHs

from Huckins et al. (11)c from Booij et al. (14)d from Hofmans (15)e

analyte pKowa Rs (L/d)b log KSPMD t1/2 (day) log KSPMD t1/2 (day) log KSPMD t1/2 (day)

acenaphthylene 4.08 2.3 3.62 6.1 3.8 9.3 3.7 7phenanthrene 4.46 3.8 4.47 26.3 4.07 10.6 4.01 92-methylphenanthrene 4.86 3.35f - - 4.36 23.4 4.31 20.81-methylphenanthrene 5.08 3.35f - - 4.52 33.8 4.46 29.53-methylphenanthrene 5.15 3.35f - - 4.58 38.0 4.51 32.8fluoranthene 5.2 3.6 4.68 45.0 4.61 38.5 4.54 32.8pyrene 5.3 4.5 4.79 46.4 4.69 36.5 4.6 30.3chrysene 5.61 3.7 5.32* 191 4.91 75.2 4.78 55.3

a pKOW values as reported by Huckins et al. (12) except for 1-, 2-, and 3-methylphenanthrene, which are from Howard and Meylan (13). b RS at10 °C as reported by Huckins et al. (12). c SPMD half-lifes calculated according to eq 1 using listed RS and measured pKSPMD from Huckins et al.(12) (- signifies no measured pKSPMD available and * signifies a known low bias as equilibrium was not reached). d SPMD half-lifes calculatedaccording to eq 1 using listed RS and pKSPMD values estimated from KOW values using regression models from Booij et al. (15) as described in thetext. e SPMD half-lifes calculated according to eq 1 using listed RS and pKSPMD values estimated from KOW values using regression models fromHofmans (16) as described in the text. f RS estimated as the mean of those reported by Huckins for the other PAHs listed.

t1/2 ) (0.693KSPMDVSPMD)/RS (1)

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west location). This is contrary to theory, which predicts thatlower flow velocities could only lead to lower SPMD residueswhen all other variables remain constant (1). Althoughbiofouling might have contributed some inter-canister biasto the results, EST indicated that there were no qualitativedifferences in the degree of biofouling on the SPMDs fromthe three deployment locations. Thus, in the final analysis,the only piece of evidence conflicting with interpreting theresults of this study as reflecting concentration gradientsalong the deployment transect is the fact that no trend wasobserved in the acenaphthylene results (Figure 2). Thus, theweight of evidence supports the observed differences asreflecting real differences in dissolved water column con-centrations, which might be attributable to trends in TSS(which was not monitored) or a vestige of the plume fromthe POTW outfall located 6.5 mi upstream of the deploymentsite.

If it is accepted that the observed differences in SPMDresidues reflected real differences in water column concen-trations, the results clearly point out the danger in assuminghomogeneous or “well-mixed” concentrations in even a smallchannelized river relatively removed from the impact of pointsources. Thus, attempting to characterize chemical gradientsin natural systems (e.g., rivers) on the basis of two-pointcomparisons will be subject to a certain amount of random-ness reflecting spatial variability in water column concentra-tions (i.e., sample heterogeneity). This heterogeneity will alsoimpact estimates of flux derived from single-point deter-minations (i.e., the estimated flux will depend on where thesingle measurement is made). In this study, the differencesin chemical-specific total flux calculated for the Long TomRiver using the results from the three different SPMD canistersranged from approximately 10% (phenanthrene) to 54%(pyrene). The overall point here is not that the individualcanister/location-specific measurements are in themselvesinaccurate, but that they should not be assumed to reflectconcentrations at other points within a natural aqueoussystem without benefit of extensive data supporting such anassumption. Regardless, the most thorough approach re-quires multi-point sampling in order to characterize spatialvariability (i.e., sample heterogeneity). Although SPMDs havean advantage over grab sampling in that they provide time-weighted-average concentrations, they provide no advantageover grab sampling when it comes to accounting for spatialvariability, and so this factor cannot be dismissed wheninterpreting the results from field deployments.

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Alvarez, D. A.; Cranor, W. L.; Clark, R. C.; Mogensen, B. B. Environ.Sci. Technol. 2002, 36, 85-91.

(2) Huckins, J. N.; Petty, J. D.; Lebo, J. A.; Orazio, C. E.; Clark, R. C.;Gibson, V. A. SPMD Technology Tutorial, 3rd ed.; http://wwwaux.cerc.cr.usgs.gov/SPMD/SPMD-Tech_Tutorial.htm (ac-cessed January 21, 2002).

(3) Petty, J. D.; Orazio, C. E.; Huckins, J. N.; Gale, R. W.; Lebo, J. A.;Meadows, J. C.; Echols, K. R.; Cranor, W. L. J. Chromatogr. A2000, 879, 83-95.

(4) Huckins, J. N.; Petty, J. D.; Lebo, J. A.; Orazio, C. E.; Prest, H. F.;Tillitt, D. E.; Ellis, G. S.; Johnson, B. T.; Manuweera, G. K.Semipermeable membrane devices (SPMDs) for the concentra-tion and assessment of bioavailable organic contaminants inaquatic environments. In Techniques in Aquatic Toxicology;Ostrander, G. K., Ed.; Lewis Publishers: Boca Raton, FL, 1996;Chapter 34.

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(10) Shoven, H. A. Monitoring Dioxin Levels in Maine Rivers withSemipermeable Membrane Devices. Masters Thesis, Universityof Maine, Orono, ME, 2001.

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(12) Huckins, J. N.; Petty, J. D.; Orazio, C. E.; Lebo, J. A.; Clark, R. C.;Gibson, V. L.; Gala, W. R.; Echols, K. R. Environ. Sci. Technol.1999, 33, 3918-3923.

(13) Howard, P. H.; Meylan, W. M. Handbook of Physical Propertiesof Organic Chemicals; Lewis Publishers: New York, 1997.

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1998, 17 (7), 1236-1245.(16) Hofmans, H. E. Numerical Modelling of the Exchange Kinetics

of Semi-permeable Membrane Devices. Masters Thesis, Uni-versity of Utrecht, Netherlands Institute for Sea Research, ABDen Burg, The Netherlands, 1998.

Received for review July 29, 2002. Revised manuscript re-ceived December 26, 2002. Accepted January 7, 2003.

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